Disaster Management in Malaysia: An Application Framework of Integrated Routing Application for Emergency Response Management System.
2009 International Conference of Soft Computing and Pattern Recognition
Disaster Management in Malaysia:
An Application Framework of Integrated Routing Application for Emergency Response Management
System
Safiza Suhana Kamal Baharin. Abdul Samad Shibghatullah . Zahriah Othman
Department of Software Engineering
FTMK, Universiti Teknikal Malaysia Melaka (UTeM),
76109 Durian Tunggal, Melaka, Malaysia
{safiza, samad, zahriah}@utem.edu.my
Abstract—Malaysia has experienced various disasters either
natural or manmade disaster. One of the critical phases in
Disaster Management System life cycle is response phase. In
this phase, connectivity analysis such as a navigation service to
help emergency rescue (ER) units reach at disaster area on
time is necessary. Nowadays, commercial navigation system
seems not appropriate to be used by ER units as they have
different preferences. In addition, location information that is
vital was not fully utilized in disaster management, especially
in doing multi-task analysis. Thus, the real potential of GIS
technology in managing spatial data including real-time
(moving objects) data of ER units may influence the quality of
the service. However, the services should be supported by a
good data model. In order to eliminate inappropriate
information, incomplete data, and overloaded information
from Database Management System (DBMS) sent to the user,
this paper will present the framework of integrated routing
application for emergency response units embedded with
context-aware.
Figure 1. Disaster Management System Life Cycle
Practically all ER services resort to use phone and paper
maps for communication and collaboration in decision
making process when they work on group. According to [3],
spatial information can facilitate identification of impending
disaster, provide directions to a disaster area or assist in
developing logistics for ensuring assistance reaches at
disaster area. Here a logical question has been arises “whether it is possible to integrate spatial data and user
preferences in navigation analysis to coordinate the multitask/ role of emergency response units?“. The question arises
as in response phase there are multiple emergency services
such as hospital, police and fire department will take part
[19].
Keywords-component; moving objects, context-aware, spatial
DBMS, Emergency Response Management System, dataware
house, route analysis
I.
INTRODUCTION
Disaster is incident that occurs in a sudden manner, complex
in nature, resulting in a loss of lives, damages to property or
the environment as well as affecting the daily activities of
local community [4]. Disaster may happen anytime,
anywhere and unavoidable. However, the impact and loses
of disaster can be reduced through effective management of
disaster information. The effective management here means
provide a tool for Emergency Response (ER) units to reach
at disaster area at the right time supported by appropriate
information. Fig. 1 shows that disaster management system
addresses 4 distinct phases, a) prevention and mitigation, b)
preparedness, c) response, and d) recovery and rehabilitation.
During disaster, time is critical. Information of moving
object such as police cars, ambulances and fire trucks
become important to drive the analyzing task including
connectivity analysis. Although GIS application has been
used in disaster management, it was designed for individual
usage such as evacuation [15], and different phases of
disaster such as mitigation and preparedness [5],[17] and
monitoring/ visualization [8], or only for specific task [9].
978-0-7695-3879-2/09 $26.00 © 2009 IEEE
DOI 10.1109/SoCPaR.2009.144
II.
RESPONSE PHASE AND CONNECTIVITY ANALYSIS
Based on the current approach, an ER unit has to guess,
estimate and make decision without adequate information.
This action will cost time, money, and lives [13]. In Disaster
Management, an incident is reported to the Command Centre
and multiple public agencies such as fire brigade, hospital,
police and municipality are prompted and gathered to form a
response team. All of these organizations have their own
information and communication resources. Although there
are an effort to standardize the communication technology
(e.g. 999), the information system (e.g. application, database)
of each organizations are not integrated [1],[16], and not
allowed information exchange within/cross department.
Thus, commander of each organization can retrieve
information via their own control room only. ER
733
716
management requires collaboration and integration to
facilitate complementary and coherent action by all partners
to ensure the effectiveness of emergency management
resources and execution of activities. Unfortunately, all of
those criteria are rarely seen in current situation or even
completely missing.
III.
DISASTER MANAGEMENT IN MALAYSIA
In Malaysia, the organization of Emergency Management
(EM) and decision making process during a disaster could be
divided into 3 different levels of scale, which are Level I,
Level II and Level III [6] (see Table 1). In order to handle
disaster effectively, a Disaster Management and Relief
Committee (DMRC) are established at federal, state, and
district level, which responsible on policy, tactical and
operational coordination level. Figure 2. shows the flow of
movement phase of ER units. Fig. 3 shows the Disaster
Management in Malaysia. According to this perspective, we
divide the user of this system into two categories, which are
static users (People at Disaster Operating Control Centre
(DOCC)) and moving users (People on the field or On Scene
Command Post (OSCP)). There is less research focusing on
operational level especially the management of ER units.
Due to different preference of each ER unit’s agency, they
tend to have their own data and system. However, each of
the application are/may referring to the same data (e.g. road,
location of accident, type of disaster, wind direction, land
use). Providing the same information through different
application is time consuming in term of data preparing,
formatting and query as the info are not relevant and cannot
be used anymore. The information that is retrieved from the
application sometimes is dedicated for all ER usage
including for general usage (e.g. use by public user) (Fig. 4).
Currently much of the moving objects information is
visualized as row data without processing. Various systems
exist that allow the dynamic display of moving objects [14].
Most of the systems are not adaptive to an elaborated context
[3],[10]. However, to support the decision-making process,
the systems should be able to visualize results of an analysis
with respect to the context of the user. This paper proposes a
Framework of Integrated Routing Application for
Emergency Response Management System that shows how
Database Management System (DBMS) could aid in
decision making process by providing appropriate
information (route network) based on multi-user preferences
(e.g. polices, ambulances and fire brigades).
TABLE I.
Disaster
Level
Level I
Level II
Level III
Figure 2. Flow of movement phase of ER units
Figure 3.
Disaster Management In Malaysia
DISASTER LEVEL IN MALAYSIA
Description
Figure 4. Example of Different Role with Same Data Sources
Localized emergency : where local resources are
adequate to manage the disaster response (DDMRC)
Emergency affected more than 2 areas and require aid
and support from outside. (SDMRC)
Disaster is complex in nature and affect areas
spanning over other states. (NDMRC)
IV. THE USE OF M OVING OBJECT DATA, LOCATION
INFORMATION, CONTEXT DATA, AND NAVIGATION IN
EMERGENCY RESPONSE SYSTEM
Information preparation is the key to determine the
successfulness of emergency rescue task to avoid confusion
because of too many information or less information is
provided. The application of NADDI by MACRES uses the
717
734
identified during requirement analysis. We divide our model
into four packages which are user, network, event and route.
The user package contains the information related to the
user (as moving objects) such as user’s background (e.g.
work schedule, jobs responsibility, and role), environment
context (e.g. location, time, environment’s condition or
weather) or social environment (e.g. traffic condition). The
network represents the spatial data which contains geometry
data (e.g. SDO_GEOMETRY in Oracle Spatial), the Event
package contains the environment information (e.g. disaster
type, location of incident and blocked area). And the last
package is route which is results from connectivity analysis
provided to the users. In order to provide the information to
the right person, at the right place and on the right time,
context information is applied. Stick to the definition of
[2][1], there are 4 elements of context that important to this
research; user identity, location, time and task [2]. This
research applied the context-aware preference model that is
Aspect-Scale-Context (ASC) model [18] and using data
cubes in organizing the preference.
Spatial DBMS is a main component of this system, that
allow maintenance of data (spatial or non-spatial) into
multiple and integrated model (such as medical model, fire
department model, police model, etc). Spatial DBMS
manages moving object data model that contains simple
feature of vector data. In order to represent a moving point,
we refer to the moving object representation on [11]. We
described our Moving Object and Context Data for
Emergency Response Management System as Fig. 8. It is
combination of spatial, context, and temporal data. There are
two main services provided by data warehouse to the users
which are analysis and reporting service that influence to the
decision making process.
sensor technology, GPS, GIS, Remote Sensing to get realtime data shows that the latest technology has been adapted
in disaster management. However, the technology and
resources was not fully utilized between organizations. For
example, the location data, and other spatial data (e.g.
flooded area) that has topological relationship cannot be
analyzed due lack of tools and data management. Moreover,
the moving point information is used only for visual
monitoring and tracking. We believe that loses in disaster
can be minimized if first responder reach at disaster location
with fastest and supported by a ‘good’ analysis capabilities.
Besides that, in order to send information to a right user and
at a right time, user preference information on road network
is useful as a context data. Although we have commercial
navigation system like Garmin, Mio, and Tom Tom that can
be used by rescue team [13] but it is still not enough and
appropriate as it is not consider the context of the ER units.
There are navigation applications capable to add blocking
area and traffic jam info to re-routing based on dynamic
changes as [7], unfortunately, less consideration had been
given to the users of the system, who may use the
information. Thus, we proposed to enhance the data model
and application because public users have different
preference or context compared to ER units. The application
must not only focus on dynamic changes on the data but also
it should take into consideration the dynamic changes of user
preferences. Field of area include on this research is moving
data, context and connectivity analysis (navigation).
V.
MOTIVATION EXAMPLE
To illustrate the involvement and important of managing
moving objects in road network combining with contextaware technology, let’s consider the following scenario. A
burning house at location B was reported. An ambulance and
fire truck has been assigned to that location. Let’s say that
the fastest route to location B from current location (says A)
of ambulance and fire trucks are through node 1, 2, 3 and 4
as shown in Fig. 5. However, node 3 is blocked by flood that
can only be accessed by a vehicle exceed than 4 tones such
as a fire truck (Fig. 6). Then the system suggests a new route
(e.g. node 1, 6, 5, and 4) to ambulance and fire truck.
Without applying context, the system does not take into
consideration the user who requires that information. The
system assumes that information is for everyone. From this
example shows that the information of new route is not
applicable and relevant to fire truck because the old route
still valid for the fire truck since the weight more than 4
tones.
VI.
Figure 5. Suggested route without
blocked node
Figure 6. Suggested route with
blocked node
OVERALL ARCHITECTURE
Fig. 7 shows the overall architecture of Moving Object and
Context-aware DBMS for an efficient emergency response
management. The application framework supports multiple
time-critical users. With the proposed framework,
heterogeneous information can be accessed by different
users. The data originate from data model is transformed
into a DBMS (e.g. Oracle). An entity on this model is
Figure 7. Overall Architecture
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735
Some examples of such analyses should be useful and
helpful in the decision making process are i) the shortest path
based on traffic information (construction, traffic jam,
accident, etc.), ii) determine the number of units for each
check point (based on the number of victims), iii) define a
suitable hospital (based on victims’ conditions, which might
vary from non-stable condition, such as outpatient, to an ICU
case caused decision should be changed on the way to the
hospital), and iv) ad-hoc decision (based on uncertainty
situation such as wind direction, river location, and
implement proximity and position analysis, fencing services,
navigation service, tracking service, [12]). The real users of
this application are decision makers or Emergency
Commander who locates in DOCC. We use the GIS to
visualizing the location of ER units and we are using Oracle
Map Viewer (MapViewer).
[4]
[5]
[6]
[7]
[8]
VII. FUTURE WORK AND CONCLUSION
[9]
This research aims at developing a conceptual framework
of integrated routing application for emergency response
management systems with focusing on management of ER
units. This framework is expected to help greatly in the
decision making process for emergency response systems.
The research hypothesis is that a Spatial DBMS (with an
appropriate spatial schema, indexing techniques, and
operations) can drastically improve the effective
management and analysis of moving objects in route
analysis. The integration of context information into the
model should provide further flexibility in querying and
visualizing data. The next steps in this research are to
develop dimensional data model at RTDW and integrate the
context data and moving object data to be used in analyzing
task. Using this approach, we believe that the proposed
model could aid and improve the decision making process,
especially in emergency situations.
[10]
[11]
[12]
[13]
[14]
OPERATIONAL COORDINATION IN EMERGENCY
RESPONSE
[15]
Spatial
Context
Temporal
Figure 8. Types of Data in Operational Coordination
[16]
REFERENCES
[1]
[2]
[3]
[17]
A. Abdul Rahman, and S. Zlatanova, “Pre-Hospital Location Based
Services (LBS) For Emergency Management”, In: E. Fendel, M.
Rumor, (Eds.); Proceedings Of UDMS'06 Aalborg, pages 11.4911.57, 2006.
A.Dey and G.Abowd.,“Towards a better understands of context and
context awareness”, In CHI 2000 Workshop on the What, Who,
Where, When, Why and How of the Context Awareness, 2000.
B.I.J., Siljee, I.E. Bosloper, and J.A.G. Nijhuis, “A Classification
Framework for storage and retrieval of context”, K1-04 Workshop on
[18]
[19]
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Modelling and Retrieval of Context, CEUR, Vol. 114, ISSN 16130073, 2004.
C.Umar, “Disaster mitigation support and management in Malaysia”,
unpublished, 2007.
E. Tsui, “Initial Response to Complex Emergencies and Natural
Disasters”, In Emergency Relief Operations, Kevin M. Cahill (ed.),
Fordham University Press and The Center for International Health
and Cooperation, New York, 32-54, 2003.
I. Mohamed Shaluf and F. Ahamadun, “Technological disaster
orevention – the case of Malaysia”, Disaster Prevention and
Management, vol. 15, No. 5, 2006, pp. 789-792, Emerald Group
Publishing Limited, doi 10.1108/09653560610712720.
I.A. Musliman, A.Abdul Rahman and V.Coors, “Modeling dynamic
weight for 3D navigation routing”, Proceeding of Map Asia 2007, 1416 August 2007, KLCC, Malaysia.
I. Rauschert, P. Agrawal, R. Sharma, S. Fuhrmann, I. Brewer, A.
MacEachren, H. Wang and G. Cai, “Designing a human-centered,
multimodal GIS interface to support emergency management”, paper
presented at GIS’02, McLean, VA, November 8-9, 2002.
L.D. Plessis, “A review of effective flood forecasting, warning and
response system for application in South Africa”, Water SA, Vol. 28
No. 2, pp. 129-38, 2002.
M. Sheleiby, M.R. Malek, A. Alesheikh, and P. Amirian, “Automatic
Map Scaling in Car Navigation Systems Using Context-aware
Computing”, World Applied Sciences Journal 3 (Supple 1): pp. 101106, ISSN 1818-4952, 2008.
M. Vazirgiannis and O. Wolfson, “A Spatiotemporal model and
language for moving objects on road networks”, C.S. Jensen et al.
(Eds.): SSTD 2001, LNCS 2121, Springer-Verlag Berlin Heidelberg
pp. 20-35, 2001.
R. Togt, E. Beinat, S. Zlatanova and H.J. Scholten, “Location
interoperability services for medical emergency operations during
disasters”, in P.J.M. van Oosterom, S.Zlatanova and E.M. Fendel
(eds), Geoinformation for disaster management, Springer-Verlag
Heidelberg, pp. 1127-1141, 2006.
S.S. Kamal Baharin and N.Suryana, The importance of managing
context and moving object data for emergency management systems.
In M Sulaiman, NS Herman, E Kasmuri & S Salam (Eds.),
International Conference on Engineering and ICT. Engineering and
ICT: Meeting the challenges of advanced manufacturing, Melaka:
Universiti Teknikal Malaysia Melaka, pp. 327-334, 2007.
S. Diehl, and J. van der Heide, “Geo-information breaks through
sector think”, in: PJM van Oosterom, S Zlatanova & EM Fendel
(Eds.), Geo-information for disaster management, Springer Verlag,
Heidelberg, pages 85-108, 2005.
S. Pu and S. Zlatanova, “Evacuation route calculation of inner
buildings”, in: van Oosterom, Zlatanova & Fendel (Eds.), Geoinformation for disaster management, Springer Verlag, Heidelberg,
pp. 1143-1161, 2005.
S. Zlatanova, D. Holweg, and M. Stratakis, “Framework for MultiRisk Emergency Response”, In: C.V. Tao and J. Li (Eds.); ISPRS
Book Series, Volume 4, Advances in Mobile Mapping Technology,
pages 159-171, 2007.
S.A. Mohamed Hashim, “National disaster and remote sensing in
Malaysia”, slide presentation at 2nd JPTM meeting, Bangkok,
Thailand, unpublished, 2006.
T. Strang, C. Linnhoff-Poppien and K. Frank, “CoOL: a context
ontology language to enable contextual interoperability”, in 4th IFIP
WG 6.1 International conference on distributed applications and
interoperable systems (DAIS2003), Vol. 2893, pp. 236-247, 2003.
W. Xu, “Ontologies for Disaster Management Response”, Lecture
Notes in Geoinformation and Cartography, Li, J., Zlatanova, S., and
Fabbri, A.G., (eds), In Geomatics Solution for Disaster Management,
Springer Berlin Heidelberg, 2007.
Disaster Management in Malaysia:
An Application Framework of Integrated Routing Application for Emergency Response Management
System
Safiza Suhana Kamal Baharin. Abdul Samad Shibghatullah . Zahriah Othman
Department of Software Engineering
FTMK, Universiti Teknikal Malaysia Melaka (UTeM),
76109 Durian Tunggal, Melaka, Malaysia
{safiza, samad, zahriah}@utem.edu.my
Abstract—Malaysia has experienced various disasters either
natural or manmade disaster. One of the critical phases in
Disaster Management System life cycle is response phase. In
this phase, connectivity analysis such as a navigation service to
help emergency rescue (ER) units reach at disaster area on
time is necessary. Nowadays, commercial navigation system
seems not appropriate to be used by ER units as they have
different preferences. In addition, location information that is
vital was not fully utilized in disaster management, especially
in doing multi-task analysis. Thus, the real potential of GIS
technology in managing spatial data including real-time
(moving objects) data of ER units may influence the quality of
the service. However, the services should be supported by a
good data model. In order to eliminate inappropriate
information, incomplete data, and overloaded information
from Database Management System (DBMS) sent to the user,
this paper will present the framework of integrated routing
application for emergency response units embedded with
context-aware.
Figure 1. Disaster Management System Life Cycle
Practically all ER services resort to use phone and paper
maps for communication and collaboration in decision
making process when they work on group. According to [3],
spatial information can facilitate identification of impending
disaster, provide directions to a disaster area or assist in
developing logistics for ensuring assistance reaches at
disaster area. Here a logical question has been arises “whether it is possible to integrate spatial data and user
preferences in navigation analysis to coordinate the multitask/ role of emergency response units?“. The question arises
as in response phase there are multiple emergency services
such as hospital, police and fire department will take part
[19].
Keywords-component; moving objects, context-aware, spatial
DBMS, Emergency Response Management System, dataware
house, route analysis
I.
INTRODUCTION
Disaster is incident that occurs in a sudden manner, complex
in nature, resulting in a loss of lives, damages to property or
the environment as well as affecting the daily activities of
local community [4]. Disaster may happen anytime,
anywhere and unavoidable. However, the impact and loses
of disaster can be reduced through effective management of
disaster information. The effective management here means
provide a tool for Emergency Response (ER) units to reach
at disaster area at the right time supported by appropriate
information. Fig. 1 shows that disaster management system
addresses 4 distinct phases, a) prevention and mitigation, b)
preparedness, c) response, and d) recovery and rehabilitation.
During disaster, time is critical. Information of moving
object such as police cars, ambulances and fire trucks
become important to drive the analyzing task including
connectivity analysis. Although GIS application has been
used in disaster management, it was designed for individual
usage such as evacuation [15], and different phases of
disaster such as mitigation and preparedness [5],[17] and
monitoring/ visualization [8], or only for specific task [9].
978-0-7695-3879-2/09 $26.00 © 2009 IEEE
DOI 10.1109/SoCPaR.2009.144
II.
RESPONSE PHASE AND CONNECTIVITY ANALYSIS
Based on the current approach, an ER unit has to guess,
estimate and make decision without adequate information.
This action will cost time, money, and lives [13]. In Disaster
Management, an incident is reported to the Command Centre
and multiple public agencies such as fire brigade, hospital,
police and municipality are prompted and gathered to form a
response team. All of these organizations have their own
information and communication resources. Although there
are an effort to standardize the communication technology
(e.g. 999), the information system (e.g. application, database)
of each organizations are not integrated [1],[16], and not
allowed information exchange within/cross department.
Thus, commander of each organization can retrieve
information via their own control room only. ER
733
716
management requires collaboration and integration to
facilitate complementary and coherent action by all partners
to ensure the effectiveness of emergency management
resources and execution of activities. Unfortunately, all of
those criteria are rarely seen in current situation or even
completely missing.
III.
DISASTER MANAGEMENT IN MALAYSIA
In Malaysia, the organization of Emergency Management
(EM) and decision making process during a disaster could be
divided into 3 different levels of scale, which are Level I,
Level II and Level III [6] (see Table 1). In order to handle
disaster effectively, a Disaster Management and Relief
Committee (DMRC) are established at federal, state, and
district level, which responsible on policy, tactical and
operational coordination level. Figure 2. shows the flow of
movement phase of ER units. Fig. 3 shows the Disaster
Management in Malaysia. According to this perspective, we
divide the user of this system into two categories, which are
static users (People at Disaster Operating Control Centre
(DOCC)) and moving users (People on the field or On Scene
Command Post (OSCP)). There is less research focusing on
operational level especially the management of ER units.
Due to different preference of each ER unit’s agency, they
tend to have their own data and system. However, each of
the application are/may referring to the same data (e.g. road,
location of accident, type of disaster, wind direction, land
use). Providing the same information through different
application is time consuming in term of data preparing,
formatting and query as the info are not relevant and cannot
be used anymore. The information that is retrieved from the
application sometimes is dedicated for all ER usage
including for general usage (e.g. use by public user) (Fig. 4).
Currently much of the moving objects information is
visualized as row data without processing. Various systems
exist that allow the dynamic display of moving objects [14].
Most of the systems are not adaptive to an elaborated context
[3],[10]. However, to support the decision-making process,
the systems should be able to visualize results of an analysis
with respect to the context of the user. This paper proposes a
Framework of Integrated Routing Application for
Emergency Response Management System that shows how
Database Management System (DBMS) could aid in
decision making process by providing appropriate
information (route network) based on multi-user preferences
(e.g. polices, ambulances and fire brigades).
TABLE I.
Disaster
Level
Level I
Level II
Level III
Figure 2. Flow of movement phase of ER units
Figure 3.
Disaster Management In Malaysia
DISASTER LEVEL IN MALAYSIA
Description
Figure 4. Example of Different Role with Same Data Sources
Localized emergency : where local resources are
adequate to manage the disaster response (DDMRC)
Emergency affected more than 2 areas and require aid
and support from outside. (SDMRC)
Disaster is complex in nature and affect areas
spanning over other states. (NDMRC)
IV. THE USE OF M OVING OBJECT DATA, LOCATION
INFORMATION, CONTEXT DATA, AND NAVIGATION IN
EMERGENCY RESPONSE SYSTEM
Information preparation is the key to determine the
successfulness of emergency rescue task to avoid confusion
because of too many information or less information is
provided. The application of NADDI by MACRES uses the
717
734
identified during requirement analysis. We divide our model
into four packages which are user, network, event and route.
The user package contains the information related to the
user (as moving objects) such as user’s background (e.g.
work schedule, jobs responsibility, and role), environment
context (e.g. location, time, environment’s condition or
weather) or social environment (e.g. traffic condition). The
network represents the spatial data which contains geometry
data (e.g. SDO_GEOMETRY in Oracle Spatial), the Event
package contains the environment information (e.g. disaster
type, location of incident and blocked area). And the last
package is route which is results from connectivity analysis
provided to the users. In order to provide the information to
the right person, at the right place and on the right time,
context information is applied. Stick to the definition of
[2][1], there are 4 elements of context that important to this
research; user identity, location, time and task [2]. This
research applied the context-aware preference model that is
Aspect-Scale-Context (ASC) model [18] and using data
cubes in organizing the preference.
Spatial DBMS is a main component of this system, that
allow maintenance of data (spatial or non-spatial) into
multiple and integrated model (such as medical model, fire
department model, police model, etc). Spatial DBMS
manages moving object data model that contains simple
feature of vector data. In order to represent a moving point,
we refer to the moving object representation on [11]. We
described our Moving Object and Context Data for
Emergency Response Management System as Fig. 8. It is
combination of spatial, context, and temporal data. There are
two main services provided by data warehouse to the users
which are analysis and reporting service that influence to the
decision making process.
sensor technology, GPS, GIS, Remote Sensing to get realtime data shows that the latest technology has been adapted
in disaster management. However, the technology and
resources was not fully utilized between organizations. For
example, the location data, and other spatial data (e.g.
flooded area) that has topological relationship cannot be
analyzed due lack of tools and data management. Moreover,
the moving point information is used only for visual
monitoring and tracking. We believe that loses in disaster
can be minimized if first responder reach at disaster location
with fastest and supported by a ‘good’ analysis capabilities.
Besides that, in order to send information to a right user and
at a right time, user preference information on road network
is useful as a context data. Although we have commercial
navigation system like Garmin, Mio, and Tom Tom that can
be used by rescue team [13] but it is still not enough and
appropriate as it is not consider the context of the ER units.
There are navigation applications capable to add blocking
area and traffic jam info to re-routing based on dynamic
changes as [7], unfortunately, less consideration had been
given to the users of the system, who may use the
information. Thus, we proposed to enhance the data model
and application because public users have different
preference or context compared to ER units. The application
must not only focus on dynamic changes on the data but also
it should take into consideration the dynamic changes of user
preferences. Field of area include on this research is moving
data, context and connectivity analysis (navigation).
V.
MOTIVATION EXAMPLE
To illustrate the involvement and important of managing
moving objects in road network combining with contextaware technology, let’s consider the following scenario. A
burning house at location B was reported. An ambulance and
fire truck has been assigned to that location. Let’s say that
the fastest route to location B from current location (says A)
of ambulance and fire trucks are through node 1, 2, 3 and 4
as shown in Fig. 5. However, node 3 is blocked by flood that
can only be accessed by a vehicle exceed than 4 tones such
as a fire truck (Fig. 6). Then the system suggests a new route
(e.g. node 1, 6, 5, and 4) to ambulance and fire truck.
Without applying context, the system does not take into
consideration the user who requires that information. The
system assumes that information is for everyone. From this
example shows that the information of new route is not
applicable and relevant to fire truck because the old route
still valid for the fire truck since the weight more than 4
tones.
VI.
Figure 5. Suggested route without
blocked node
Figure 6. Suggested route with
blocked node
OVERALL ARCHITECTURE
Fig. 7 shows the overall architecture of Moving Object and
Context-aware DBMS for an efficient emergency response
management. The application framework supports multiple
time-critical users. With the proposed framework,
heterogeneous information can be accessed by different
users. The data originate from data model is transformed
into a DBMS (e.g. Oracle). An entity on this model is
Figure 7. Overall Architecture
718
735
Some examples of such analyses should be useful and
helpful in the decision making process are i) the shortest path
based on traffic information (construction, traffic jam,
accident, etc.), ii) determine the number of units for each
check point (based on the number of victims), iii) define a
suitable hospital (based on victims’ conditions, which might
vary from non-stable condition, such as outpatient, to an ICU
case caused decision should be changed on the way to the
hospital), and iv) ad-hoc decision (based on uncertainty
situation such as wind direction, river location, and
implement proximity and position analysis, fencing services,
navigation service, tracking service, [12]). The real users of
this application are decision makers or Emergency
Commander who locates in DOCC. We use the GIS to
visualizing the location of ER units and we are using Oracle
Map Viewer (MapViewer).
[4]
[5]
[6]
[7]
[8]
VII. FUTURE WORK AND CONCLUSION
[9]
This research aims at developing a conceptual framework
of integrated routing application for emergency response
management systems with focusing on management of ER
units. This framework is expected to help greatly in the
decision making process for emergency response systems.
The research hypothesis is that a Spatial DBMS (with an
appropriate spatial schema, indexing techniques, and
operations) can drastically improve the effective
management and analysis of moving objects in route
analysis. The integration of context information into the
model should provide further flexibility in querying and
visualizing data. The next steps in this research are to
develop dimensional data model at RTDW and integrate the
context data and moving object data to be used in analyzing
task. Using this approach, we believe that the proposed
model could aid and improve the decision making process,
especially in emergency situations.
[10]
[11]
[12]
[13]
[14]
OPERATIONAL COORDINATION IN EMERGENCY
RESPONSE
[15]
Spatial
Context
Temporal
Figure 8. Types of Data in Operational Coordination
[16]
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[1]
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[3]
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